The Black-capped Petrel or Diablotin Pterodroma hasitata has a fragmented and declining population estimated at c.1,000 breeding pairs. On land, the species nests underground in steep ravines with dense understorey vegetation. The only confirmed breeding sites are located in the mountain ranges of Hispaniola in the Caribbean, where habitat loss and degradation are continuing threats. Other nesting populations may still remain undiscovered but, to locate them, laborious in situ nest searches must be conducted over expansive geographical areas. To focus nest-search efforts more efficiently, we analysed the environmental characteristics of Black-capped Petrel nesting habitat and modeled suitable habitat on Hispaniola using openly available environmental datasets. We used a univariate generalized linear model to compare the habitat characteristics of active Black-capped Petrel nests sites with those of potentially available sites (i.e. random pseudo-absences). Elevation, distance to coast, and the influence of tree cover and density emerged as important environmental variables. We then applied multivariate generalized linear models to these environmental variables that showed a significant relationship with petrel nesting activity. We used the top performing model of habitat suitability model to create maps of predicted suitability for Hispaniola. In addition to areas of known petrel activity, the model identified possible nesting areas for Black-capped Petrels in habitats not previously considered suitable. Based on model results, we estimated the total area of predicted suitable nesting habitat for Black-capped Petrels on Hispaniola and found that forest loss due to hurricanes, forest fires, and encroachment from agriculture had severely decreased availability of predicted suitable habitat between 2000 and 2018.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0959270920000490","usgsCitation":"Satge, Y.G., Rupp, E., Brown, A.J., and Jodice, P.G., 2021, Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss: Bird Conservation International, v. 31, no. 4, p. 573-590, https://doi.org/10.1017/S0959270920000490.","productDescription":"18 p.","startPage":"573","endPage":"590","ipdsId":"IP-115786","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454339,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0959270920000490","text":"Publisher Index Page"},{"id":436651,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FWJPBD","text":"USGS data release","linkHelpText":"Nesting habitat suitability for the Black-capped Petrel Pterodroma hasitata on Hispaniola, Supplementary Material"},{"id":395771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Dominican Republic, Haiti","otherGeospatial":"Hispaniola","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.09326171875,\n 18.823116948090494\n ],\n [\n -69.2138671875,\n 19.621892180319374\n ],\n [\n -71.136474609375,\n 20.159098270646936\n ],\n [\n -72.916259765625,\n 20.24158281954221\n ],\n [\n -73.71826171874999,\n 19.766703551716976\n ],\n [\n -74.92675781249999,\n 18.396230138028827\n ],\n [\n -73.201904296875,\n 17.602139123350838\n ],\n [\n -71.47705078125,\n 17.45547257997284\n ],\n [\n -68.79638671875,\n 17.90556881196468\n ],\n [\n -68.21411132812499,\n 18.3336694457713\n ],\n [\n -68.09326171875,\n 18.823116948090494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Satge, Y. G.","contributorId":275774,"corporation":false,"usgs":false,"family":"Satge","given":"Y.","email":"","middleInitial":"G.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rupp, E.","contributorId":265431,"corporation":false,"usgs":false,"family":"Rupp","given":"E.","email":"","affiliations":[],"preferred":false,"id":834274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, A. J.","contributorId":197185,"corporation":false,"usgs":false,"family":"Brown","given":"A.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":834275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834276,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215758,"text":"70215758 - 2021 - Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner","interactions":[],"lastModifiedDate":"2021-01-19T16:39:46.16129","indexId":"70215758","displayToPublicDate":"2020-10-26T08:13:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7183,"text":"Limnology and Oceanography Methods","active":true,"publicationSubtype":{"id":10}},"title":"Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner","docAbstract":"Mangrove forests have adapted to sea level rise (SLR) increases by maintaining their forest floor elevation via belowground root growth and surface sediment deposits. Researchers use surface elevation tables (SETs) to monitor surface elevation change (SEC) in mangrove forests, after which this information is used to assess SLR resiliency or to dictate active forest management for vulnerable systems. This method requires significant investments in terms of time and human resources and is limited in the number of points it can measure per plot. We use a low‐cost, portable terrestrial laser scanning (TLS) system to assess SEC for three mangrove forests on Pohnpei Island (Federated States of Micronesia). Cloth simulation filtering was used for ground detection, after which results were refined by filtering points using angular orientation. Digital elevation models then were generated via kriging interpolation for data collected in 2017 and 2019, after which the heights of corresponding points were compared across years. Extreme elevation changes, due to disturbances such as footprints or fallen logs, were removed using interquartile range analysis. The TLS‐obtained average SEC ranged between −6.92 and +6.01 mm, which exhibited an average consistency of 72% when compared to simultaneously collected SET data (root mean square error = 1.36 mm). We contend that this approach represents an improvement over the manual method, where very few points typically are used, that is, ≅ 36 points vs. ≅ 30,000 points in the case of TLS, and could contribute to improved monitoring and management of these rapidly changing forest environments.
Many estuarine ecosystems and the fish communities that inhabit them have undergone substantial changes in the past several decades, largely due to multiple interacting stressors that are often of anthropogenic origin. Few are more impactful than droughts, which are predicted to increase in both frequency and severity with climate change. In this study, we examined over five decades of fish monitoring data from the San Francisco Estuary, California, USA, to evaluate the resistance and resilience of fish communities to disturbance from prolonged drought events. High resistance was defined by the lack of decline in species occurrence from a wet to a subsequent drought period, while high resilience was defined by the increase in species occurrence from a drought to a subsequent wet period. We found some unifying themes connecting the multiple drought events over the 50‐yr period. Pelagic fishes consistently declined during droughts (low resistance), but exhibit a considerable amount of resiliency and often rebound in the subsequent wet years. However, full recovery does not occur in all wet years following droughts, leading to permanently lower baseline numbers for some pelagic fishes over time. In contrast, littoral fishes seem to be more resistant to drought and may even increase in occurrence during dry years. Based on the consistent detrimental effects of drought on pelagic fishes within the San Francisco Estuary and the inability of these fish populations to recover in some years, we conclude that freshwater flow remains a crucial but not sufficient management tool for the conservation of estuarine biodiversity.
The scarcity of strong ground motion records presents a challenge for making reliable performance assessments of tall buildings whose seismic design is controlled by large-magnitude and close-distance earthquakes. This challenge can be addressed using broadband ground-motion simulation methods to generate records with site-specific characteristics of large-magnitude events. In this paper, simulated site-specific earthquake seismograms, developed through a related project that was organized through the Southern California Earthquake Center (SCEC) Ground Motion Simulation Validation (GMSV) Technical Activity Group, are used for nonlinear response history analyses of two archetype tall buildings for sites in San Francisco, Los Angeles, and San Bernardino. The SCEC GMSV team created the seismograms using the Broadband Platform (BBP) simulations for five site-specific earthquake scenarios. The two buildings are evaluated using nonlinear dynamic analyses under comparable record suites selected from the simulated BBP catalog and recorded motions from the NGA-West database. The collapse risks and structural response demands (maximum story drift ratio, peak floor acceleration, and maximum story shear) under the BBP and NGA suites are compared. In general, this study finds that use of the BBP simulations resolves concerns about estimation biases in structural response analysis which are caused by ground motion scaling, unrealistic spectral shapes, and overconservative spectral variations. While there are remaining concerns that strong coherence in some kinematic fault rupture models may lead to an overestimation of velocity pulse effects in the BBP simulations, the simulations are shown to generally yield realistic pulse-like features of near-fault ground motion records.
","language":"English","publisher":"Wiley","doi":"10.1002/eqe.3364","usgsCitation":"Zhong, K., Lin, T., Deierlein, G., Graves, R., Silva, F., and Luco, N., 2021, Tall building performance-based seismic design using SCEC broadband platform site-specific ground motion simulations: Earthquake Engineering and Structural Dynamics, v. 50, no. 1, p. 81-98, https://doi.org/10.1002/eqe.3364.","productDescription":"18 p.","startPage":"81","endPage":"98","ipdsId":"IP-119067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":454358,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2346/88059","text":"External Repository"},{"id":387857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles, San Bernardino, San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.39790916442873,\n 37.78178983833927\n ],\n [\n -122.3886823654175,\n 37.78178983833927\n ],\n [\n -122.3886823654175,\n 37.78921753609959\n ],\n [\n -122.39790916442873,\n 37.78921753609959\n ],\n [\n -122.39790916442873,\n 37.78178983833927\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.26359510421753,\n 34.05214385256302\n ],\n [\n -118.25709342956542,\n 34.05214385256302\n ],\n [\n -118.25709342956542,\n 34.0581704783008\n ],\n [\n -118.26359510421753,\n 34.0581704783008\n ],\n [\n -118.26359510421753,\n 34.05214385256302\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.29613304138182,\n 34.09673784258847\n ],\n [\n -117.27553367614746,\n 34.09673784258847\n ],\n [\n -117.27553367614746,\n 34.11812893261633\n ],\n [\n -117.29613304138182,\n 34.11812893261633\n ],\n [\n -117.29613304138182,\n 34.09673784258847\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhong, Kuanshi","contributorId":264127,"corporation":false,"usgs":false,"family":"Zhong","given":"Kuanshi","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":820928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Ting","contributorId":264128,"corporation":false,"usgs":false,"family":"Lin","given":"Ting","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":820929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deierlein, Greg","contributorId":264129,"corporation":false,"usgs":false,"family":"Deierlein","given":"Greg","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":820930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":820931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Silva, Fabio","contributorId":264130,"corporation":false,"usgs":false,"family":"Silva","given":"Fabio","email":"","affiliations":[{"id":54387,"text":"SCEC","active":true,"usgs":false}],"preferred":false,"id":820932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820933,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216567,"text":"70216567 - 2021 - Artificial nightlight alters the predator-prey dynamics of an apex carnivore","interactions":[],"lastModifiedDate":"2021-02-04T00:03:38.074751","indexId":"70216567","displayToPublicDate":"2020-10-18T09:01:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Artificial nightlight alters the predator-prey dynamics of an apex carnivore","docAbstract":"Artificial nightlight is increasingly recognized as an important environmental disturbance that influences the habitats and fitness of numerous species. However, its effects on wide‐ranging vertebrates and their interactions remain unclear. Light pollution has the potential to amplify land‐use change, and as such, answering the question of how this sensory stimulant affects behavior and habitat use of species valued for their ecological roles and economic impacts is critical for conservation and land‐use planning. Here, we combined satellite‐derived estimates of light pollution, with GPS‐data from cougars Puma concolor (n = 56), mule deer Odocoileus hemionus (n = 263) and locations of cougar‐killed deer (n = 1562 carcasses), to assess the effects of light exposure on mammal behavior and predator–prey relationships across wildland–urban gradients in the southwestern United States. Our results indicate that deer used the anthropogenic environments to access forage and were more active at night than their wildland conspecifics. Despite higher nightlight levels, cougars killed deer at the wildland–urban interface, but hunted them in the relatively darkest locations. Light had the greatest effect of all covariates on where cougars killed deer at the wildland–urban interface. Both species exhibited functional responses to light pollution at fine scales; individual cougars and deer with less light exposure increasingly avoided illuminated areas when exposed to greater radiance, whereas deer living in the wildland–urban interface selected elevated light levels. We conclude that integrating estimates of light pollution into ecological studies provides crucial insights into how the dynamic human footprint can alter animal behavior and ecosystem function across spatial scales.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.05251","usgsCitation":"Ditmer, M.A., Stoner, D.C., Francis, C.D., Barber, J.R., Forester, J.D., Choate, D.M., Ironside, K.E., Longshore, K., Hersey, K.R., Larson, R.T., McMillan, B., Olson, D., Andreasen, A.M., Beckmann, J., Holton, B.P., Messmer, T., and Carter, N., 2021, Artificial nightlight alters the predator-prey dynamics of an apex carnivore: Ecography, v. 44, no. 2, p. 1492-161, https://doi.org/10.1111/ecog.05251.","productDescription":"16 p.","startPage":"1492","endPage":"161","ipdsId":"IP-121575","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":454367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.05251","text":"Publisher Index Page"},{"id":380780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, 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University","active":true,"usgs":false}],"preferred":false,"id":805626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forester, James D.","contributorId":194334,"corporation":false,"usgs":false,"family":"Forester","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":805627,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Choate, David M.","contributorId":207778,"corporation":false,"usgs":false,"family":"Choate","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":805628,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ironside, Kristen E.","contributorId":245207,"corporation":false,"usgs":false,"family":"Ironside","given":"Kristen","email":"","middleInitial":"E.","affiliations":[{"id":24583,"text":"former USGS 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M.","contributorId":245211,"corporation":false,"usgs":false,"family":"Andreasen","given":"Alyson","email":"","middleInitial":"M.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":805635,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Beckmann, Jon P.","contributorId":73098,"corporation":false,"usgs":true,"family":"Beckmann","given":"Jon P.","affiliations":[],"preferred":false,"id":805653,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Holton, Brandon P.","contributorId":245212,"corporation":false,"usgs":false,"family":"Holton","given":"Brandon","email":"","middleInitial":"P.","affiliations":[{"id":49123,"text":"NPS - Grand Canyon National Park","active":true,"usgs":false}],"preferred":false,"id":805636,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Carter, Neil H.","contributorId":245214,"corporation":false,"usgs":false,"family":"Carter","given":"Neil H.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":805638,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Messmer, Terry A.","contributorId":245213,"corporation":false,"usgs":false,"family":"Messmer","given":"Terry A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":805637,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70219196,"text":"70219196 - 2021 - Signatures of hydrologic function across the critical zone observatory network","interactions":[],"lastModifiedDate":"2021-03-30T12:05:44.485187","indexId":"70219196","displayToPublicDate":"2020-10-18T06:50:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Signatures of hydrologic function across the critical zone observatory network","docAbstract":"Despite a multitude of small catchment studies, we lack a deep understanding of how variations in critical zone architecture lead to variations in hydrologic states and fluxes. This study characterizes hydrologic dynamics of 15 catchments of the U.S. Critical Zone Observatory (CZO) network where we hypothesized that our understanding of subsurface structure would illuminate patterns of hydrologic partitioning. The CZOs collect data sets that characterize the physical, chemical, and biological architecture of the subsurface, while also monitoring hydrologic fluxes such as streamflow, precipitation, and evapotranspiration. For the first time, we collate time series of hydrologic variables across the CZO network and begin the process of examining hydrologic signatures across sites. We find that catchments with low baseflow indices and high runoff sensitivity to storage receive most of their precipitation as rain and contain clay‐rich regolith profiles, prominent argillic horizons, and/or anthropogenic modifications. In contrast, sites with high baseflow indices and low runoff sensitivity to storage receive the majority of precipitation as snow and have more permeable regolith profiles. The seasonal variability of water balance components is a key control on the dynamic range of hydraulically connected water in the critical zone. These findings lead us to posit that water balance partitioning and streamflow hydraulics are linked through the coevolution of critical zone architecture but that much work remains to parse these controls out quantitatively.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR026635","usgsCitation":"Wlostowski, A.N., Molotch, N.P., Anderson, S.P., Brantley, S.L., Chorover, J., Dralle, D., Kumar, P., Li, L., Lohse, K.A., Mallard, J., McIntosh, J.C., Murphy, S.F., Parrish, E., Safeeq, M., Seyfried, M., Shi, Y., and Harman, C., 2021, Signatures of hydrologic function across the critical zone observatory network: Water Resources Research, v. 57, no. 3, e2019WR026635, 28 p., https://doi.org/10.1029/2019WR026635.","productDescription":"e2019WR026635, 28 p.","ipdsId":"IP-117846","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019wr026635","text":"Publisher Index Page"},{"id":384750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Wlostowski, Adam N. 0000-0001-5703-9916","orcid":"https://orcid.org/0000-0001-5703-9916","contributorId":191365,"corporation":false,"usgs":false,"family":"Wlostowski","given":"Adam","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":813172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Molotch, Noah P. 0000-0003-4733-8060","orcid":"https://orcid.org/0000-0003-4733-8060","contributorId":203466,"corporation":false,"usgs":false,"family":"Molotch","given":"Noah","email":"","middleInitial":"P.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":813173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Suzanne P. 0000-0002-6796-6649","orcid":"https://orcid.org/0000-0002-6796-6649","contributorId":172732,"corporation":false,"usgs":false,"family":"Anderson","given":"Suzanne","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":813174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brantley, Susan L. 0000-0003-4320-2342","orcid":"https://orcid.org/0000-0003-4320-2342","contributorId":184201,"corporation":false,"usgs":false,"family":"Brantley","given":"Susan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":813175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chorover, Jon 0000-0001-9497-0195","orcid":"https://orcid.org/0000-0001-9497-0195","contributorId":139472,"corporation":false,"usgs":false,"family":"Chorover","given":"Jon","email":"","affiliations":[],"preferred":false,"id":813176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dralle, David 0000-0002-1944-2103","orcid":"https://orcid.org/0000-0002-1944-2103","contributorId":256752,"corporation":false,"usgs":false,"family":"Dralle","given":"David","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":813177,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Praveen 0000-0002-4787-0308","orcid":"https://orcid.org/0000-0002-4787-0308","contributorId":256753,"corporation":false,"usgs":false,"family":"Kumar","given":"Praveen","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":813178,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Li, Li 0000-0002-1641-3710","orcid":"https://orcid.org/0000-0002-1641-3710","contributorId":197290,"corporation":false,"usgs":false,"family":"Li","given":"Li","affiliations":[],"preferred":false,"id":813179,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lohse, Kathleen A. 0000-0003-1779-6773","orcid":"https://orcid.org/0000-0003-1779-6773","contributorId":196995,"corporation":false,"usgs":false,"family":"Lohse","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":813180,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mallard, John 0000-0002-0494-9024","orcid":"https://orcid.org/0000-0002-0494-9024","contributorId":256757,"corporation":false,"usgs":false,"family":"Mallard","given":"John","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":813181,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McIntosh, Jennifer C. 0000-0001-5055-4202","orcid":"https://orcid.org/0000-0001-5055-4202","contributorId":150557,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":813182,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":813183,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Parrish, Eric","contributorId":256760,"corporation":false,"usgs":false,"family":"Parrish","given":"Eric","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":813184,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Safeeq, Mohammad 0000-0003-0529-3925","orcid":"https://orcid.org/0000-0003-0529-3925","contributorId":77814,"corporation":false,"usgs":false,"family":"Safeeq","given":"Mohammad","email":"","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":813185,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Seyfried, Mark 0000-0001-8081-0713","orcid":"https://orcid.org/0000-0001-8081-0713","contributorId":256763,"corporation":false,"usgs":false,"family":"Seyfried","given":"Mark","email":"","affiliations":[{"id":51849,"text":"United States Department of Agriculture - Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":813186,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Shi, Yuning 0000-0003-0118-5847","orcid":"https://orcid.org/0000-0003-0118-5847","contributorId":256765,"corporation":false,"usgs":false,"family":"Shi","given":"Yuning","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":813187,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Harman, Ciaran 0000-0002-3185-002X","orcid":"https://orcid.org/0000-0002-3185-002X","contributorId":242780,"corporation":false,"usgs":false,"family":"Harman","given":"Ciaran","email":"","affiliations":[{"id":48526,"text":"Department of Environmental Health and Engineering, Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":813188,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70254939,"text":"70254939 - 2021 - Hierarchical computing for hierarchical models in ecology","interactions":[],"lastModifiedDate":"2024-06-12T00:14:56.560958","indexId":"70254939","displayToPublicDate":"2020-10-17T19:13:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Hierarchical computing for hierarchical models in ecology","docAbstract":"Postfire shifts in vegetation composition will have broad ecological impacts. However, information characterizing postfire recovery patterns and their drivers are lacking over large spatial extents. In this analysis, we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of postfire, dual-season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field-measured patterns of re-vegetation, and (3) identify seasonally specific drivers of postfire rates of NDVI recovery. Rates of postfire NDVI recovery were calculated for both the GS and SCS for more than 12,500 burned points across the western United States. Points were partitioned into faster and slower rates of NDVI recovery using thresholds derived from field plot data (n = 230) and their associated rates of NDVI recovery. We found plots with conifer saplings had significantly higher SCS NDVI recovery rates relative to plots without conifer saplings, while plots with ≥50% grass/forbs/shrubs cover had significantly higher GS NDVI recovery rates relative to plots with <50%. GS rates of NDVI recovery were best predicted by burn severity and anomalies in postfire maximum temperature. SCS NDVI recovery rates were best explained by aridity and growing degree days. This study is the most extensive effort, to date, to track postfire forest recovery across the western United States. Isolating patterns and drivers of evergreen recovery from deciduous recovery will enable improved characterization of forest ecological condition across large spatial scales.
The eastern Adirondack Highlands of northern New York host dozens of iron oxide-apatite (IOA) deposits containing magnetite and rare earth element (REE)-bearing apatite. We use new aeromagnetic, aeroradiometric, ground gravity, and sample petrophysical and geochemical data to image and understand these deposits and their geologic framework. Aeromagnetic total field data reflect highly magnetic leucogranite host rock and major structures that likely served as fluid conduits for the hydrothermal system. Bandpass filtering of the aeromagnetic data reveals individual deposits that were verified in the field or from historical records. A three-dimensional inversion for magnetic susceptibility images these deposits at depth, allowing inference of plunge directions and relative size. Radiometric data highlight variations in the surface geology and several large tailings piles that contain REE-bearing apatite. Within the host rock, eTh (equivalent Th), K and the eTh/K ratio are variable with high eTh/K near several of the IOA deposits. Areas with elevated K or low eTh/K representing potassic alteration appear to be rare; instead elevated eTh/K ratios likely reflect widespread sodic alteration overprinting potassic alteration. Bouguer gravity anomalies show limited correspondence to the surface geology, radiometric data, or magnetic data, but do exhibit ~10-km wide highs in areas where deposits are observed. Two-dimensional forward models of the gravity and magnetic data show that deeper dense material beneath the leucogranite is quantitatively feasible. If these dense rocks represent intrusions that were emplaced or still cooling at the time of mineralization, they may have served as a heat source that helped to drive the hydrothermal system. Combining datasets, we find that deposits occur towards the distal ends of major structures within the host leucogranite and mostly above gravity highs. The geophysical modeling thus suggests that IOA deposits formed in structural, thermal, and chemical traps near the distal ends of the hydrothermal system.
","language":"English","publisher":"Society for Exploration Geophysics","doi":"10.1190/geo2019-0783.1","usgsCitation":"Shah, A.K., Taylor, R.D., Walsh, G.J., and Phillips, J., 2021, Integrated geophysical imaging of rare-earth-element-bearing iron oxide-apatite deposits in the eastern Adirondack Highlands, New York: Geophysics, v. 86, no. 1, p. B37-B54, https://doi.org/10.1190/geo2019-0783.1.","productDescription":"18 p.","startPage":"B37","endPage":"B54","ipdsId":"IP-117777","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":454380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1190/geo2019-0783.1","text":"Publisher Index Page"},{"id":380582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.2451171875,\n 43.42100882994726\n ],\n [\n -73.6083984375,\n 43.42100882994726\n ],\n [\n -73.6083984375,\n 44.809121700077355\n ],\n [\n -76.2451171875,\n 44.809121700077355\n ],\n [\n -76.2451171875,\n 43.42100882994726\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805129,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":245004,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805130,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":805131,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232558,"text":"70232558 - 2021 - Nutrient limitation of phytoplankton in Chesapeake Bay: Development of an empirical approach for water-quality management","interactions":[],"lastModifiedDate":"2022-07-07T12:01:41.226961","indexId":"70232558","displayToPublicDate":"2020-10-13T06:57:47","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient limitation of phytoplankton in Chesapeake Bay: Development of an empirical approach for water-quality management","docAbstract":"Understanding the temporal and spatial roles of nutrient limitation on phytoplankton growth is necessary for developing successful management strategies. Chesapeake Bay has well-documented seasonal and spatial variations in nutrient limitation, but it remains unknown whether these patterns of nutrient limitation have changed in response to nutrient management efforts. We analyzed historical data from nutrient bioassay experiments (1992–2002) and data from long-term, fixed-site water-quality monitoring program (1990–2017) to develop empirical approaches for predicting nutrient limitation in the surface waters of the mainstem Bay. Results from classification and regression trees (CART) matched the seasonal and spatial patterns of bioassay-based nutrient limitation in the 1992–2002 period much better than two simpler, non-statistical approaches. An ensemble approach of three selected CART models satisfactorily reproduced the bioassay-based results (classification rate = 99%). This empirical approach can be used to characterize nutrient limitation from long-term water-quality monitoring data on much broader geographic and temporal scales than would be feasible using bioassays, providing a new tool for informing water-quality management. Results from our application of the approach to 21 tidal monitoring stations for the period of 2007–2017 showed modest changes in nutrient limitation patterns, with expanded areas of nitrogen-limitation and contracted areas of nutrient saturation (i.e., not limited by nitrogen or phosphorus). These changes imply that long-term reductions in nitrogen load have led to expanded areas with nutrient-limited phytoplankton growth in the Bay, reflecting long-term water-quality improvements in the context of nutrient enrichment. However, nutrient limitation patterns remain unchanged in the majority of the mainstem, suggesting that nutrient loads should be further reduced to achieve a less nutrient-saturated ecosystem.
New seismic stations added to a regional seismic network cannot be used to calculate local magnitude (
Greater Sage-Grouse (Centrocercus urophasianus; hereafter, sage-grouse) and free-roaming horses (Equus caballus) co-occur within large portions of sagebrush ecosystems within the Great Basin of western North America. In recent decades, sage-grouse populations have declined substantially while concomitant free-roaming horse populations have increased drastically. Although multiple studies have reported free-roaming horses adversely impacting native ungulate species, direct interactions between free-roaming horses and sage-grouse have not been documented previously. We compiled sage-grouse lek count data and associated ungulate observations during spring of 2010 and 2013–2018. We used Bayesian multinomial logistic models to examine the response of breeding male sage-grouse to the presence of native (i.e. mule deer, pronghorn) and non-native (i.e. cattle, free-roaming horses) ungulates on active sage-grouse leks (traditional breeding grounds). We found sage-grouse were approximately five times more likely to be present on active leks concurrent with native ungulates compared to non-native ungulates. Of the four different ungulate species, sage-grouse were least likely to be at active leks when free-roaming horses were present. Our results indicate that free-roaming horse presence at lek sites negatively influences sage-grouse lekking activity. Because sage-grouse population growth is sensitive to breeding success, disruption of leks by free-roaming horses could reduce breeding opportunities and limit breeding areas within sage-grouse habitat.
Since the beginning of the 20th century, volcano geodesy has evolved from time- and personnel-intensive methods for collecting discrete measurements to automated and/or remote tools that provide data with exceptional spatiotemporal resolution. By acknowledging and overcoming limitations related to data collection and interpretation, geodesy becomes a powerful tool for forecasting the onset and tracking the evolution of volcanic eruptions. In addition, geodetic data can be used for novel applications, such as mapping surface and topographic change due to the emplacement of volcanic deposits, detecting volcanic plumes, and constraining the properties of magmatic systems. These collective capabilities provide critical support for understanding magmatic processes at erupting volcanoes, while also offering important baseline data in advance of potential volcanic unrest. Future developments in volcano geodesy will involve not just new technology, but also advanced modeling and automated analysis methods that will provide a new understanding of the volcanic activity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Forecasting and planning for volcanic hazards, risks, and disasters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-818082-2.00003-2","usgsCitation":"Poland, M., and de Zeeuw-van Dalfsen, E., 2021, Volcano geodesy: A critical tool for assessing the state of volcanoes and their potential for hazardous eruptive activity, chap. 3 of Forecasting and planning for volcanic hazards, risks, and disasters, p. 75-115, https://doi.org/10.1016/B978-0-12-818082-2.00003-2.","productDescription":"41 p.","startPage":"75","endPage":"115","ipdsId":"IP-108637","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":397705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":838968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":838969,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217753,"text":"70217753 - 2021 - Variation of lead isotopic composition and atomic weight in terrestrial materials (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2021-02-01T17:02:04.460805","indexId":"70217753","displayToPublicDate":"2020-10-01T10:56:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Variation of lead isotopic composition and atomic weight in terrestrial materials (IUPAC Technical Report)","docAbstract":"The isotopic composition and atomic weight of lead are variable in terrestrial materials because its three heaviest stable isotopes are stable end-products of the radioactive decay of uranium (238U to 206Pb; 235U to 207Pb) and thorium (232Th to 208Pb). The lightest stable isotope, 204Pb, is primordial. These variations in isotope ratios and atomic weights provide useful information in many areas of science, including geochronology, archaeology, environmental studies, and forensic science. While elemental lead can serve as an abundant and homogeneous isotopic reference, deviations from the isotope ratios in other lead occurrences limit the accuracy with which a standard atomic weight can be given for lead. In a comprehensive review of several hundred publications and analyses of more than 8000 samples, published isotope data indicate that the lowest reported lead atomic weight of a normal terrestrial materials is 206.1462 ± 0.0028 (k = 2), determined for a growth of the phosphate mineral monazite around a garnet relic from an Archean high-grade metamorphic terrain in north-western Scotland, which contains mostly 206Pb and almost no 204Pb. The highest published lead atomic weight is 207.9351 ± 0.0005 (k = 2) for monazite from a micro-inclusion in a garnet relic, also from a high-grade metamorphic terrain in north-western Scotland, which contains almost pure radiogenic 208Pb. When expressed as an interval, the lead atomic weight is [206.14, 207.94]. It is proposed that a value of 207.2 be adopted for the single lead atomic-weight value for education, commerce, and industry, corresponding to previously published conventional atomic-weight values.
","language":"English","publisher":"DeGruyter","doi":"10.1515/pac-2018-0916","usgsCitation":"Zhu, X., Benefield, J., Coplen, T.B., Gao, Z., and Holden, N.E., 2021, Variation of lead isotopic composition and atomic weight in terrestrial materials (IUPAC Technical Report): Pure and Applied Chemistry, v. 93, no. 1, p. 155-166, https://doi.org/10.1515/pac-2018-0916.","productDescription":"12 p.","startPage":"155","endPage":"166","ipdsId":"IP-114839","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":454412,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1615597","text":"Publisher Index Page"},{"id":382847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhu, Xiang-Kun 0000-0002-8407-6883","orcid":"https://orcid.org/0000-0002-8407-6883","contributorId":248595,"corporation":false,"usgs":false,"family":"Zhu","given":"Xiang-Kun","email":"","affiliations":[{"id":49957,"text":"Institute of Geology, Chinese Academy of Geological Sciences, Beijing 100037, China","active":true,"usgs":false}],"preferred":false,"id":809479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benefield, Jacqueline 0000-0001-9124-2424 jbenefield@usgs.gov","orcid":"https://orcid.org/0000-0001-9124-2424","contributorId":190135,"corporation":false,"usgs":true,"family":"Benefield","given":"Jacqueline","email":"jbenefield@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":809480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":809481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gao, Zhaofu 0000-0001-7110-6126","orcid":"https://orcid.org/0000-0001-7110-6126","contributorId":248596,"corporation":false,"usgs":false,"family":"Gao","given":"Zhaofu","email":"","affiliations":[{"id":49957,"text":"Institute of Geology, Chinese Academy of Geological Sciences, Beijing 100037, China","active":true,"usgs":false}],"preferred":false,"id":809482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holden, Norman E.","contributorId":189167,"corporation":false,"usgs":false,"family":"Holden","given":"Norman","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":809483,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220860,"text":"70220860 - 2021 - Evaluating the effects of downscaled climate projections on groundwater storage and simulated base-flow contribution to the North Fork Red River and Lake Altus, southwest Oklahoma (USA)","interactions":[],"lastModifiedDate":"2021-05-27T11:59:40.427832","indexId":"70220860","displayToPublicDate":"2020-10-01T07:25:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the effects of downscaled climate projections on groundwater storage and simulated base-flow contribution to the North Fork Red River and Lake Altus, southwest Oklahoma (USA)","docAbstract":"Potential effects of projected climate variability on base flow and groundwater storage in the North Fork Red River aquifer, Oklahoma (USA), were estimated using downscaled climate model data coupled with a numerical groundwater-flow model. The North Fork Red River aquifer discharges groundwater to the North Fork Red River, which provides inflow to Lake Altus. To approximate future conditions, Coupled Model Intercomparison Project Phase 5 climate data were downscaled to the watershed and a time-series of scaling factors were developed and interpolated for three climate scenarios (central tendency, warmer and drier, and less warm and wetter) representing future climate conditions for the period 2045–2074. These scaling factors were then applied to a soil-water-balance model to produce groundwater recharge and evapotranspiration estimates. A MODFLOW groundwater-flow model of the North Fork Red River aquifer used the scaled recharge and evapotranspiration data to estimate changes in base flow and water-surface elevation of Lake Altus. Compared to a baseline scenario, the mean percent change in annual base flow during 2045–2074 was −10.8 and −15.9% for the central tendency and warmer/drier scenarios, respectively; the mean percent change in annual base flow for the less-warm/wetter scenario was +15.7%. The mean annual percent change in groundwater storage for the central tendency, warmer/drier, and less-warm/wetter climate scenarios and the baseline are −2.7, −3.2, and +3.0%, respectively. The range of outcomes from the climate scenarios may be influenced by variability in the downscaled climate data for precipitation more than for temperature.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02230-x","usgsCitation":"Labriola, L., Ellis, J., Gangopadhyay, S., Pruitt, T., Kirstetter, P., and Hong, Y., 2021, Evaluating the effects of downscaled climate projections on groundwater storage and simulated base-flow contribution to the North Fork Red River and Lake Altus, southwest Oklahoma (USA): Hydrogeology Journal, v. 28, no. 8, p. 2903-2916, https://doi.org/10.1007/s10040-020-02230-x.","productDescription":"14 p.","startPage":"2903","endPage":"2916","ipdsId":"IP-111529","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":436658,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91DWW91","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used in simulations of selected climate scenarios of groundwater availability in the North Fork Red River aquifer, southwestern Oklahoma"},{"id":385978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.00927734375,\n 33.706062655101206\n ],\n [\n -94.37255859375,\n 33.706062655101206\n ],\n [\n -94.37255859375,\n 35.47856499535729\n ],\n [\n -97.00927734375,\n 35.47856499535729\n ],\n [\n -97.00927734375,\n 33.706062655101206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Labriola, L.G. 0000-0002-5096-2940","orcid":"https://orcid.org/0000-0002-5096-2940","contributorId":216625,"corporation":false,"usgs":true,"family":"Labriola","given":"L.G.","email":"","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, J.H. 0000-0001-7161-3136 jellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7161-3136","contributorId":196287,"corporation":false,"usgs":true,"family":"Ellis","given":"J.H.","email":"jellis@usgs.gov","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":816475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pruitt, Tom","contributorId":257612,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":816476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirstetter, Pierre","contributorId":258774,"corporation":false,"usgs":false,"family":"Kirstetter","given":"Pierre","affiliations":[{"id":52282,"text":"School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73072, USA","active":true,"usgs":false}],"preferred":false,"id":816477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hong, Yang","contributorId":258775,"corporation":false,"usgs":false,"family":"Hong","given":"Yang","affiliations":[{"id":52282,"text":"School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73072, USA","active":true,"usgs":false}],"preferred":false,"id":816478,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222937,"text":"70222937 - 2021 - Select techniques for detecting and quantifying seepage from unlined canals","interactions":[],"lastModifiedDate":"2021-08-10T15:51:00.827832","indexId":"70222937","displayToPublicDate":"2020-09-30T10:39:31","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"ST-2020-19144-01","title":"Select techniques for detecting and quantifying seepage from unlined canals","docAbstract":"Canal seepage losses affect the ability of water conveyance structures to maximize efficiency and can be a precursor to canal failure. Identification and quantification of canal seepage out of unlined canals is a complex interaction affected by geology, canal stage, operations, embankment geometry, siltation, animal burrows, structures, and other physical characteristics. Seepage out of unlined canals can be coarsely estimated using a mass balance-type approach (water in minus water out with the difference assumed to be a combination of seepage and evapotranspiration). More sophisticated methods are used in some instances but are typically limited efforts aimed at quantifying seepage in a specific location.
Seepage is generally broken out into two categories: diffuse and concentrated (or focused) seepage. Diffuse seepage is where the seepage discharges relatively constant over a given area, whereas concentrated (point discharge source) seepage discharges along preferentially focused areas. Diffuse seepage typically occurs in homogeneous conditions where the amount of water flowing into the subsurface is controlled by soil permeability and canal stage. Conversely, concentrated seepage occurs in areas of heterogeneous conditions where water flows into bedrock fractures, rodent burrows or other pre-existing discrete flow-paths. Concentrated seepage can also develop in the advent of sudden or excessive increases in hydraulic gradient which can lead to heaving, cracking, and development of backward erosion piping flow-paths. Concentrated and diffuse seepage can lead to seeps, in this case, a surface expression of water fed by irrigation water on canal embankment or at distal regions away from the canal.
This report focuses on work funded by the Research and Development Office from Fiscal Year 2016 through 2021 and the references provided pertain primarily to those efforts. This report also provides a generalized framework for how and when to investigate seepage out of an unlined canal based on the type of seepage, level of understanding about the seepage locations, geology, and knowledge of the subsurface conditions. The various methods used to locate seeps and quantify canal seepage are discussed in further detail, with references provided for the reader.
The following seepage investigation scenarios are discussed within the report:
1. Idealized workflow insensitive to time with highest quality data required
2. General workflow sensitive to time with highest quality data required
3. General workflow insensitive to time with lowest cost items preceding more costly techniques
4. Newly developed concentrated seep(s), concern about consequences (time sensitive)
5. Newly developed or rapidly increasing diffuse seepage, concern about consequences (time sensitive)
6. Existing concentrated seep(s), limited concern about consequences, poor geologic understanding
7. Existing concentrated seep(s), limited concern about consequences, good geologic understanding
8. Existing diffuse seepage, limited concern about consequences, poor geologic understanding
9. Existing diffuse seepage, limited concern about consequences, good geologic understanding
A workflow is given for each scenario which details recommended steps and the order in which those steps should be taken to maximize efficiency and data quality. The various seepage investigation techniques and estimated costs are discussed in more detail later in this report.
The next step is to take the data collected from the various methods and incorporate them into canal operations models to optimize deliveries. This step could also include the development of 3D seepage models to better understand the larger-scale groundwater-surface water interactions and how they are affected by the water delivery system.
","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Lindenbach, E.J., Kang, J.B., Rittgers, J.B., and Naranjo, R.C., 2021, Select techniques for detecting and quantifying seepage from unlined canals: Final Report ST-2020-19144-01, viii, 75 p.","productDescription":"viii, 75 p.","ipdsId":"IP-122681","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":387819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387793,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/research/projects/download_product.cfm?id=2955"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lindenbach, Evan J.","contributorId":263642,"corporation":false,"usgs":false,"family":"Lindenbach","given":"Evan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":820920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kang, Jong Beom","contributorId":263643,"corporation":false,"usgs":false,"family":"Kang","given":"Jong","email":"","middleInitial":"Beom","affiliations":[],"preferred":false,"id":820921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rittgers, Justin B.","contributorId":263644,"corporation":false,"usgs":false,"family":"Rittgers","given":"Justin","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":820922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820873,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218827,"text":"70218827 - 2021 - A multiproxy database of western North American Holocene paleoclimate records","interactions":[],"lastModifiedDate":"2023-08-23T14:49:34.683705","indexId":"70218827","displayToPublicDate":"2020-09-30T07:05:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"A multiproxy database of western North American Holocene paleoclimate records","docAbstract":"Holocene climate reconstructions are useful for understanding the diverse features and spatial heterogeneity of past and future climate change. Here we present a database of western North American Holocene paleoclimate records. The database gathers paleoclimate time series from 184 terrestrial and marine sites, including 381 individual proxy records. The records span at least 4000 of the last 12 000 years (median duration of 10 725 years) and have been screened for resolution, chronologic control, and climate sensitivity. Records were included that reflect temperature, hydroclimate, or circulation features. The database is shared in the machine readable Linked Paleo Data (LiPD) format and includes geochronologic data for generating site-level time-uncertain ensembles. This publicly accessible and curated collection of proxy paleoclimate records will have wide research applications, including, for example, investigations of the primary features of ocean–atmospheric circulation along the eastern margin of the North Pacific and the latitudinal response of climate to orbital changes. The database is available for download at https://doi.org/10.6084/m9.figshare.12863843.v1 (Routson and McKay, 2020).
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-13-1613-2021","usgsCitation":"Routson, C.C., Kaufman, D.S., McKay, N.P., Erb, M., Arcusa, S.H., Brown, K., Kirby, M.E., Marsicek, J., Anderson, R.S., Jimenez-Moreno, G., Rodysill, J.R., Lachniet, M.S., Fritz, S.C., Bennett, J., Goman, M.F., Metcalfe, S.E., Galloway, J.M., Schoups, G., Wahl, D., Morris, J.L., Staines-Urias, F., Dawson, A., Shuman, B.N., Gavin, D.G., Munroe, J.S., and Cumming, B.F., 2021, A multiproxy database of western North American Holocene paleoclimate records: Earth System Science Data, v. 13, p. 1613-1632, https://doi.org/10.5194/essd-13-1613-2021.","productDescription":"20 p.","startPage":"1613","endPage":"1632","ipdsId":"IP-121927","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":454416,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-13-1613-2021","text":"Publisher Index Page"},{"id":384408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2021-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Routson, Cody C. 0000-0001-8694-7809","orcid":"https://orcid.org/0000-0001-8694-7809","contributorId":187600,"corporation":false,"usgs":false,"family":"Routson","given":"Cody","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":812310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaufman, Darrell S. 0000-0002-7572-1414","orcid":"https://orcid.org/0000-0002-7572-1414","contributorId":28308,"corporation":false,"usgs":true,"family":"Kaufman","given":"Darrell","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":812344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKay, Nicholas P. 0000-0003-3598-5113","orcid":"https://orcid.org/0000-0003-3598-5113","contributorId":7612,"corporation":false,"usgs":true,"family":"McKay","given":"Nicholas","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":812345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erb, Michael 0000-0002-1187-952X","orcid":"https://orcid.org/0000-0002-1187-952X","contributorId":220669,"corporation":false,"usgs":false,"family":"Erb","given":"Michael","email":"","affiliations":[{"id":40222,"text":"School or Earth and Sustainability, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":812346,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arcusa, S. H. 0000-0003-0694-9623","orcid":"https://orcid.org/0000-0003-0694-9623","contributorId":255421,"corporation":false,"usgs":false,"family":"Arcusa","given":"S.","email":"","middleInitial":"H.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":812347,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Kendrick","contributorId":255444,"corporation":false,"usgs":false,"family":"Brown","given":"Kendrick","email":"","affiliations":[],"preferred":false,"id":812348,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kirby, Matthew E.","contributorId":200294,"corporation":false,"usgs":false,"family":"Kirby","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":13544,"text":"California State University, Fullerton","active":true,"usgs":false}],"preferred":false,"id":812349,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marsicek, Jeremiah","contributorId":197081,"corporation":false,"usgs":false,"family":"Marsicek","given":"Jeremiah","email":"","affiliations":[],"preferred":false,"id":812350,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Anderson, R. Scott","contributorId":47041,"corporation":false,"usgs":true,"family":"Anderson","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":812351,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jimenez-Moreno, Gonzalo 0000-0001-7185-8686","orcid":"https://orcid.org/0000-0001-7185-8686","contributorId":127413,"corporation":false,"usgs":false,"family":"Jimenez-Moreno","given":"Gonzalo","email":"","affiliations":[],"preferred":false,"id":812352,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rodysill, Jessica R. 0000-0002-3602-7227 jrodysill@usgs.gov","orcid":"https://orcid.org/0000-0002-3602-7227","contributorId":207577,"corporation":false,"usgs":true,"family":"Rodysill","given":"Jessica","email":"jrodysill@usgs.gov","middleInitial":"R.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":812353,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lachniet, M. S. 0000-0001-5250-0144","orcid":"https://orcid.org/0000-0001-5250-0144","contributorId":255430,"corporation":false,"usgs":false,"family":"Lachniet","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":40182,"text":"University of Nevada Las Vegas","active":true,"usgs":false}],"preferred":false,"id":812354,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fritz, Sherilyn C.","contributorId":30155,"corporation":false,"usgs":true,"family":"Fritz","given":"Sherilyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":812355,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bennett, Joseph","contributorId":203187,"corporation":false,"usgs":false,"family":"Bennett","given":"Joseph","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":812356,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Goman, Michelle F.","contributorId":255445,"corporation":false,"usgs":false,"family":"Goman","given":"Michelle","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":812357,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Metcalfe, Sarah E.","contributorId":103555,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":812358,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Galloway, J. M. 0000-0002-4548-6396","orcid":"https://orcid.org/0000-0002-4548-6396","contributorId":255437,"corporation":false,"usgs":false,"family":"Galloway","given":"J.","email":"","middleInitial":"M.","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":812359,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schoups, G.","contributorId":255438,"corporation":false,"usgs":false,"family":"Schoups","given":"G.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":812360,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":812361,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Morris, Jesse L.","contributorId":44829,"corporation":false,"usgs":true,"family":"Morris","given":"Jesse","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":812362,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Staines-Urias, F.","contributorId":255440,"corporation":false,"usgs":false,"family":"Staines-Urias","given":"F.","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":812363,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Dawson, A.","contributorId":255441,"corporation":false,"usgs":false,"family":"Dawson","given":"A.","email":"","affiliations":[{"id":40107,"text":"Mount Royal University","active":true,"usgs":false}],"preferred":false,"id":812364,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Shuman, B. N.","contributorId":255442,"corporation":false,"usgs":false,"family":"Shuman","given":"B.","email":"","middleInitial":"N.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":812365,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Gavin, Daniel G.","contributorId":98213,"corporation":false,"usgs":true,"family":"Gavin","given":"Daniel","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":812366,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Munroe, Jeffrey S.","contributorId":24175,"corporation":false,"usgs":false,"family":"Munroe","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":880956,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Cumming, Brian F.","contributorId":172514,"corporation":false,"usgs":false,"family":"Cumming","given":"Brian","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":880957,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70216786,"text":"70216786 - 2021 - Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling","interactions":[],"lastModifiedDate":"2020-12-07T15:10:38.473531","indexId":"70216786","displayToPublicDate":"2020-09-24T09:08:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling","docAbstract":"The adverse impacts of harmful algal blooms (HABs) are increasing worldwide. Lake Erie is a North American Great Lake highly affected by cultural eutrophication and summer cyanobacterial HABs. While phosphorus loading is a known driver of bloom size, more nuanced yet crucial questions remain. For example, it is unclear what mechanisms are primarily responsible for initiating cyanobacterial dominance and subsequent biomass accumulation. To address these questions, we develop a mechanistic model describing June–October dynamics of chlorophyll a, nitrogen, and phosphorus near the Maumee River outlet, where blooms typically initiate and are most severe. We calibrate the model to a new, geostatistically-derived dataset of daily water quality spanning 2008–2017. A Bayesian framework enables us to embed prior knowledge on system characteristics and test alternative model formulations. Overall, the best model formulation explains 42% of the variability in chlorophyll a and 83% of nitrogen, and better captures bloom timing than previous models. Our results, supported by cross validation, show that onset of the major midsummer bloom is associated with about a month of water temperatures above 20 °C (occurring 19 July to 6 August), consistent with when cyanobacteria dominance is usually reported. Decreased phytoplankton loss rate is the main factor enabling biomass accumulation, consistent with reduced zooplankton grazing on cyanobacteria. The model also shows that phosphorus limitation is most severe in August, and nitrogen limitation tends to occur in early autumn. Our results highlight the role of temperature in regulating bloom initiation and subsequent loss rates, and suggest that a 2 °C increase could lead to blooms that start about 10 days earlier and grow 23% more intense.
Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations. Automatic seismic arrival detections made from standard picking methods (e.g., short‐term average/long‐term average [STA/LTA]) are fed to trained neural network models to improve automatic seismic‐arrival (pick) timing and estimate seismic‐arrival phase type and source‐station distances. These additional data are used to improve the capabilities of the NEIC associator. We compile a dataset of 1.3 million seismic‐phase arrivals that represent a globally distributed set of source‐station paths covering a range of phase types, magnitudes, and source distances. We train three separate convolutional neural network models to predict arrival time onset, phase type, and distance. We validate the performance of the trained networks on a subset of our existing dataset and further extend validation by exploring the model performance when applied to NEIC automatic pick data feeds. We show that the information provided by these models can be useful in downstream event processing, specifically in seismic‐phase association, resulting in reduced false associations and improved location estimates.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200178","usgsCitation":"Yeck, W.L., Patton, J., Ross, Z.E., Hayes, G., Guy, M.M., Ambruz, N., Shelly, D.R., Benz, H.M., and Earle, P.S., 2021, Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center: Seismological Research Letters, v. 92, no. 1, p. 4469-480, https://doi.org/10.1785/0220200178.","productDescription":"12 p.","startPage":"4469","endPage":"480","ipdsId":"IP-120508","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436665,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OHF4WL","text":"USGS data release","linkHelpText":"Waveform Data and Metadata used to National Earthquake Information Center Deep-Learning Models"},{"id":436664,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ICQPUR","text":"USGS data release","linkHelpText":"neic-machine-learning"},{"id":388157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":821548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patton, John 0000-0003-0142-5118","orcid":"https://orcid.org/0000-0003-0142-5118","contributorId":218681,"corporation":false,"usgs":true,"family":"Patton","given":"John","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ross, Zachary E.","contributorId":196001,"corporation":false,"usgs":false,"family":"Ross","given":"Zachary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":821550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guy, Michelle M. 0000-0003-3450-4656 mguy@usgs.gov","orcid":"https://orcid.org/0000-0003-3450-4656","contributorId":173432,"corporation":false,"usgs":true,"family":"Guy","given":"Michelle","email":"mguy@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ambruz, Nicholas 0000-0002-3660-3546","orcid":"https://orcid.org/0000-0002-3660-3546","contributorId":218684,"corporation":false,"usgs":true,"family":"Ambruz","given":"Nicholas","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":821554,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821555,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821556,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70214567,"text":"70214567 - 2021 - Net-spinning caddisfly distribution in large regulated rivers","interactions":[],"lastModifiedDate":"2020-12-29T21:34:43.821143","indexId":"70214567","displayToPublicDate":"2020-09-20T09:11:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Net-spinning caddisfly distribution in large regulated rivers","docAbstract":"Latitudinal patterns of biodiversity have long been a central topic in ecology and evolutionary biology. However, while most previous studies have focused on native species, little effort has been devoted to latitudinal patterns of plant invasions (with a few exceptions based on data from sparse locations). Using the most up‐to‐date worldwide native and alien plant distribution data from 801 regions (including islands), we compared invasion levels (i.e. alien richness/total richness) in the Northern and Southern Hemispheres and across continental regions and islands around the globe. Results from quantile regressions using B‐splines to model nonlinearity showed (1) declining richness with increasing latitude, although the highest alien richness occurs at around 40 degrees in both hemispheres, (2) decreasing invasion levels towards higher latitudes on islands but a unimodal pattern in invasion level in continental regions in each hemisphere, (3) significantly higher invasion levels on islands than in continental regions and (4) a greater variability in invasion levels on islands at low latitudes than on high‐latitude islands. In continental regions, only the mid‐latitudes had high variability with both low and high invasion levels. Our findings identified latitudes with invasion hotspots where management is urgently needed, and latitudes with many areas of low invasions but high conservation potential where prevention of future invasions should be the priority.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.13943","usgsCitation":"Guo, Q., Cade, B.S., Dawson, W., Essl, F., Kreft, H., Pergl, J., van Kleunen, M., Weigelt, P., Winter, M., and Pyšek, P., 2021, Latitudinal patterns of alien plant invasions: Journal of Biogeography, v. 48, no. 2, p. 253-262, https://doi.org/10.1111/jbi.13943.","productDescription":"10 p.","startPage":"253","endPage":"262","ipdsId":"IP-119112","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.13943","text":"Publisher Index Page"},{"id":383380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Guo, Qinfeng","contributorId":214263,"corporation":false,"usgs":false,"family":"Guo","given":"Qinfeng","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":810509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cade, Brian S. 0000-0001-9623-9849 cadeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9623-9849","contributorId":1278,"corporation":false,"usgs":true,"family":"Cade","given":"Brian","email":"cadeb@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dawson, Wayne","contributorId":193105,"corporation":false,"usgs":false,"family":"Dawson","given":"Wayne","email":"","affiliations":[],"preferred":false,"id":810511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Essl, Franz","contributorId":167872,"corporation":false,"usgs":false,"family":"Essl","given":"Franz","email":"","affiliations":[{"id":24846,"text":"Division of Conservation Biology, Vegetation and Landscape Ecology, University of Vienna","active":true,"usgs":false}],"preferred":false,"id":810512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kreft, Holger","contributorId":193108,"corporation":false,"usgs":false,"family":"Kreft","given":"Holger","email":"","affiliations":[],"preferred":false,"id":810513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pergl, Jan","contributorId":193109,"corporation":false,"usgs":false,"family":"Pergl","given":"Jan","email":"","affiliations":[],"preferred":false,"id":810514,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Kleunen, Mark","contributorId":193107,"corporation":false,"usgs":false,"family":"van Kleunen","given":"Mark","email":"","affiliations":[],"preferred":false,"id":810515,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weigelt, Patrick","contributorId":193111,"corporation":false,"usgs":false,"family":"Weigelt","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":810516,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Winter, Marten","contributorId":178720,"corporation":false,"usgs":false,"family":"Winter","given":"Marten","email":"","affiliations":[],"preferred":false,"id":810517,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pyšek, Petr","contributorId":251754,"corporation":false,"usgs":false,"family":"Pyšek","given":"Petr","affiliations":[{"id":17790,"text":"Czech Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":810518,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70213078,"text":"70213078 - 2021 - Resolving species boundaries in the critically imperiled freshwater mussel species, Fusconaia mitchelli (Bivalvia: Unionidae)","interactions":[],"lastModifiedDate":"2021-01-19T16:46:05.336074","indexId":"70213078","displayToPublicDate":"2020-09-02T10:03:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6485,"text":"Journal of Zoological Systematics and Evolutionary Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Resolving species boundaries in the critically imperiled freshwater mussel species, Fusconaia mitchelli (Bivalvia: Unionidae)","title":"Resolving species boundaries in the critically imperiled freshwater mussel species, Fusconaia mitchelli (Bivalvia: Unionidae)","docAbstract":"Species are a fundamental unit of biology, and defining accurate species boundaries is integral to effective conservation and management of imperiled taxa. Freshwater mussels (Bivalvia: Unionidae) are among the most imperiled groups of organisms in North America, yet species boundaries remain uncertain for many taxa. The False Spike, Fusconaia mitchelli (Simpson in Dall, 1895), is a freshwater mussel considered to be endemic to central Texas (Brazos, Colorado, and Guadalupe drainages). Recent research revealed significant intraspecific genetic variation between geographically separated populations of F. mitchelli, which could be indicative of speciation; however, small sample sizes for several of the populations precluded formal taxonomic revision. Here, we increase taxon sampling and use multilocus DNA sequence data and traditional morphometrics to re‐evaluate species boundaries in F. mitchelli. We sequenced three loci: the protein‐coding mitochondrial DNA genes cytochrome c oxidase subunit 1 and NADH dehydrogenase 1, and the nuclear internal transcribed spacer 1. Phylogenetic analyses depicted deep genetic divergence between F. mitchelli in the Guadalupe and those in the Brazos and Colorado drainages, which was further supported by available biogeographic information. Morphometric analyses and coalescent‐based species delimitation models integrating both DNA sequence and morphological data provided strong support for the divergence observed between the two geographically isolated clades of F. mitchelli. Based on these results, we revise taxonomy accordingly by elevating the junior synonym Fusconaia iheringi (Wright, 1898) to represent the Brazos and Colorado populations and restrict the distribution of F. mitchelli to the Guadalupe River drainage. Our findings may impact pending management decisions to protect F. mitchelli under the U.S. Endangered Species Act.
","language":"English","publisher":"Wiley","doi":"10.1111/jzs.12412","usgsCitation":"Smith, C.H., Johnson, N., Havlik, K., Doyle, R.D., and Randklev, C.R., 2021, Resolving species boundaries in the critically imperiled freshwater mussel species, Fusconaia mitchelli (Bivalvia: Unionidae): Journal of Zoological Systematics and Evolutionary Research, v. 59, no. 1, p. 60-77, https://doi.org/10.1111/jzs.12412.","productDescription":"18 p.","startPage":"60","endPage":"77","ipdsId":"IP-114078","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":436673,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y7K5CD","text":"USGS data release","linkHelpText":"Molecular and morphological data to resolve species boundaries in the critically imperiled freshwater mussel species, Fusconaia mitchelli"},{"id":378265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Chase H. 0000-0002-1499-0311","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":225140,"corporation":false,"usgs":false,"family":"Smith","given":"Chase","email":"","middleInitial":"H.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":798169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":205384,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":798170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Havlik, Kaitlyn","contributorId":239935,"corporation":false,"usgs":false,"family":"Havlik","given":"Kaitlyn","email":"","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":798171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doyle, Robert D.","contributorId":239937,"corporation":false,"usgs":false,"family":"Doyle","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":798172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":798173,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223224,"text":"70223224 - 2021 - Profiling lunar dust dissolution in aqueous environments: The design concept","interactions":[],"lastModifiedDate":"2021-08-18T12:42:15.472873","indexId":"70223224","displayToPublicDate":"2020-09-02T07:40:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":626,"text":"Acta Astronautica","printIssn":"0094-5765","active":true,"publicationSubtype":{"id":10}},"title":"Profiling lunar dust dissolution in aqueous environments: The design concept","docAbstract":"Published studies and internal NASA reports indicate that when native lunar dust is suspended in an aqueous solution a variety of metal and other ions are released. This release has implications for future lunar missions, ranging from effects on mission hardware, effects on life support systems, possible direct effects on human health, and effects on research experiments such as plant growth experiments, space biology experiments and any activities that may involve the use of water sourced from the lunar poles. Furthermore, such contaminants could become concentrated or chemically altered to a more hazardous form during a variety of lunar mission activities, including everything from space suit cleaning to lunar industrial materials extraction. The exact profile of the release of ions from lunar dust and the nature of the partially dissolved particles has not been explored. Any model of this dissolution must be based on an understanding of the unique micromorphology of lunar dust, including its glassy nature, agglutinate features, high surface area and the presence of small deposits of elemental iron (nanophase iron) located near the surface of the grain particles. Dust has a very high surface area available for interaction with water. For this reason, on first exposure to water, an immediate pulsed release of ions could occur, with more prolonged release taking place over months or years. The few studies that have been conducted previously have been limited in both the time scales examined and in the selection of ions that were measured. The proposed investigation is a comprehensive materials science investigation, using the most modern analytical tools to catalogue all metals given off from lunar dust in various aqueous solutions and their time profiles of release from the very short term to the very long term. The product of the proposed study will be a comprehensive database determined from NASA curated samples collected from the Apollo landing sites that can be applied to research in both living systems and non-living systems on the moon. The methods developed in the proposed study will also establish standards for analysis of lunar dust samples returned from future manned missions (Artemis and others) and future robotic missions. The knowledge gained from this basic materials science investigation will have broad impact on the design of engineered human safety and health systems.